A probabilistic model of absolute auditory thresholds and its possible physiological basis

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Abstract

Detection thresholds for auditory stimuli, specified in terms of their amplitude or level, depend on the stimulus temporal envelope and decrease with increasing stimulus duration. The neural mechanisms underlying these fundamental across-species observations are not fully understood. Here, we present a "continuous look" model, according to which the stimulus gives rise to stochastic neural detection events whose probability of occurrence is proportional to the 3rd power of the low-pass filtered, time-varying stimulus amplitude. Threshold is reached when a criterion number of events have occurred (probability summation). No long-term integration is required. We apply the model to an extensive set of thresholds measured in humans for tones of different envelopes and durations and find it to fit well. Subtle differences at long durations may be due to limited attention resources. We confirm the probabilistic nature of the detection events by analyses of simple reaction times and verify the exponent of 3 by validating model predictions for binaural thresholds from monaural thresholds. The exponent originates in the auditory periphery, possibly in the intrinsic Ca2+ cooperativity of the Ca2+ sensor involved in exocytosis from inner hair cells. It results in growth of the spike rate of auditory-nerve fibers (ANFs) with the 3rd power of the stimulus amplitude before saturating (Heil et al., J Neurosci 31:15424-15437, 2011), rather than with its square (i.e., with stimulus intensity), as is commonly assumed. Our work therefore suggests a link between detection thresholds and a key biochemical reaction in the receptor cells. © Springer Science+Business Media New York 2013.

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Heil, P., Neubauer, H., Tetschke, M., & Irvine, D. R. F. (2013). A probabilistic model of absolute auditory thresholds and its possible physiological basis. In Advances in Experimental Medicine and Biology (Vol. 787, pp. 21–29). Springer Science and Business Media, LLC. https://doi.org/10.1007/978-1-4614-1590-9_3

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